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import pickle
import pytest
import networkx as nx
sp = pytest.importorskip("scipy")
pytest.importorskip("numpy")
def test_dispatch_kwds_vs_args():
G = nx.path_graph(4)
nx.pagerank(G)
nx.pagerank(G=G)
with pytest.raises(TypeError):
nx.pagerank()
def test_pickle():
count = 0
for name, func in nx.utils.backends._registered_algorithms.items():
pickled = pickle.dumps(func.__wrapped__)
assert pickle.loads(pickled) is func.__wrapped__
try:
# Some functions can't be pickled, but it's not b/c of _dispatchable
pickled = pickle.dumps(func)
except pickle.PicklingError:
continue
assert pickle.loads(pickled) is func
count += 1
assert count > 0
assert pickle.loads(pickle.dumps(nx.inverse_line_graph)) is nx.inverse_line_graph
@pytest.mark.skipif(
"not nx.config.backend_priority.algos "
"or nx.config.backend_priority.algos[0] != 'nx_loopback'"
)
def test_graph_converter_needs_backend():
# When testing, `nx.from_scipy_sparse_array` will *always* call the backend
# implementation if it's implemented. If `backend=` isn't given, then the result
# will be converted back to NetworkX via `convert_to_nx`.
# If not testing, then calling `nx.from_scipy_sparse_array` w/o `backend=` will
# always call the original version. `backend=` is *required* to call the backend.
from networkx.classes.tests.dispatch_interface import (
LoopbackBackendInterface,
LoopbackGraph,
)
A = sp.sparse.coo_array([[0, 3, 2], [3, 0, 1], [2, 1, 0]])
side_effects = []
def from_scipy_sparse_array(self, *args, **kwargs):
side_effects.append(1) # Just to prove this was called
return self.convert_from_nx(
self.__getattr__("from_scipy_sparse_array")(*args, **kwargs),
preserve_edge_attrs=True,
preserve_node_attrs=True,
preserve_graph_attrs=True,
)
@staticmethod
def convert_to_nx(obj, *, name=None):
if type(obj) is nx.Graph:
return obj
return nx.Graph(obj)
# *This mutates LoopbackBackendInterface!*
orig_convert_to_nx = LoopbackBackendInterface.convert_to_nx
LoopbackBackendInterface.convert_to_nx = convert_to_nx
LoopbackBackendInterface.from_scipy_sparse_array = from_scipy_sparse_array
try:
assert side_effects == []
assert type(nx.from_scipy_sparse_array(A)) is nx.Graph
assert side_effects == [1]
assert (
type(nx.from_scipy_sparse_array(A, backend="nx_loopback")) is LoopbackGraph
)
assert side_effects == [1, 1]
# backend="networkx" is default implementation
assert type(nx.from_scipy_sparse_array(A, backend="networkx")) is nx.Graph
assert side_effects == [1, 1]
finally:
LoopbackBackendInterface.convert_to_nx = staticmethod(orig_convert_to_nx)
del LoopbackBackendInterface.from_scipy_sparse_array
with pytest.raises(ImportError, match="backend is not installed"):
nx.from_scipy_sparse_array(A, backend="bad-backend-name")
@pytest.mark.skipif(
"not nx.config.backend_priority.algos "
"or nx.config.backend_priority.algos[0] != 'nx_loopback'"
)
def test_networkx_backend():
"""Test using `backend="networkx"` in a dispatchable function."""
# (Implementing this test is harder than it should be)
from networkx.classes.tests.dispatch_interface import (
LoopbackBackendInterface,
LoopbackGraph,
)
G = LoopbackGraph()
G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4)])
@staticmethod
def convert_to_nx(obj, *, name=None):
if isinstance(obj, LoopbackGraph):
new_graph = nx.Graph()
new_graph.__dict__.update(obj.__dict__)
return new_graph
return obj
# *This mutates LoopbackBackendInterface!*
# This uses the same trick as in the previous test.
orig_convert_to_nx = LoopbackBackendInterface.convert_to_nx
LoopbackBackendInterface.convert_to_nx = convert_to_nx
try:
G2 = nx.ego_graph(G, 0, backend="networkx")
assert type(G2) is nx.Graph
finally:
LoopbackBackendInterface.convert_to_nx = staticmethod(orig_convert_to_nx)
def test_dispatchable_are_functions():
assert type(nx.pagerank) is type(nx.pagerank.orig_func)
@pytest.mark.skipif("not nx.utils.backends.backends")
def test_mixing_backend_graphs():
from networkx.classes.tests import dispatch_interface
G = nx.Graph()
G.add_edge(1, 2)
G.add_edge(2, 3)
H = nx.Graph()
H.add_edge(2, 3)
rv = nx.intersection(G, H)
assert set(nx.intersection(G, H)) == {2, 3}
G2 = dispatch_interface.convert(G)
H2 = dispatch_interface.convert(H)
if "nx_loopback" in nx.config.backend_priority:
# Auto-convert
assert set(nx.intersection(G2, H)) == {2, 3}
assert set(nx.intersection(G, H2)) == {2, 3}
elif not nx.config.backend_priority and "nx_loopback" not in nx.config.backends:
# G2 and H2 are backend objects for a backend that is not registered!
with pytest.raises(ImportError, match="backend is not installed"):
nx.intersection(G2, H)
with pytest.raises(ImportError, match="backend is not installed"):
nx.intersection(G, H2)
# It would be nice to test passing graphs from *different* backends,
# but we are not set up to do this yet.
def test_bad_backend_name():
"""Using `backend=` raises with unknown backend even if there are no backends."""
with pytest.raises(
ImportError, match="'this_backend_does_not_exist' backend is not installed"
):
nx.null_graph(backend="this_backend_does_not_exist")
def test_fallback_to_nx():
with pytest.warns(DeprecationWarning, match="_fallback_to_nx"):
# Check as class property
assert nx._dispatchable._fallback_to_nx == nx.config.fallback_to_nx
# Check as instance property
assert nx.pagerank.__wrapped__._fallback_to_nx == nx.config.fallback_to_nx
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